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» Learning Models for Predicting Recognition Performance
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128
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WWW
2010
ACM
15 years 10 months ago
A scalable machine-learning approach for semi-structured named entity recognition
Named entity recognition studies the problem of locating and classifying parts of free text into a set of predefined categories. Although extensive research has focused on the de...
Utku Irmak, Reiner Kraft
CVPR
2005
IEEE
16 years 5 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang
143
Voted
CRV
2009
IEEE
158views Robotics» more  CRV 2009»
15 years 10 months ago
Automated Spatial-Semantic Modeling with Applications to Place Labeling and Informed Search
This paper presents a spatial-semantic modeling system featuring automated learning of object-place relations from an online annotated database, and the application of these relat...
Pooja Viswanathan, David Meger, Tristram Southey, ...
JAIR
2006
137views more  JAIR 2006»
15 years 3 months ago
Learning Sentence-internal Temporal Relations
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
Maria Lapata, Alex Lascarides
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 3 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil